Journal Pre-proof Municipal solid waste management: Integrated analysis of environmental and economic indicators based on life cycle assessment Michel Xocaira Paes, Gerson Araujo de Medeiros, Sandro Donnnini Mancini, Ana Paula Bortoleto, José Antonio Puppim de Oliveira, Luiz Alexandre Kulay PII:
To appear in:
Journal of Cleaner Production
Received Date: 12 August 2019 Revised Date:
17 December 2019
Accepted Date: 21 December 2019
Please cite this article as: Paes MX, Araujo de Medeiros G, Mancini SD, Bortoleto AP, Puppim de Oliveira JoséAntonio, Kulay LA, Municipal solid waste management: Integrated analysis of environmental and economic indicators based on life cycle assessment, Journal of Cleaner Production (2020), doi: https://doi.org/10.1016/j.jclepro.2019.119848. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.
Author Contributions Section
All authors (Michel Xocaira Paesa, Gerson Araujo de Medeiros, Sandro Donnnini Mancini, Ana Paula Bortoleto, Jose Antonio Puppim de Oliveira and Luiz Alexandre Kulay) participated in all stages of this work, from conception to this review and final submission. We highlight some important stages: Conceptualization, Methodological Development, Software Choice, Data and Results Analysis, Writing, Drafting and Original Article, Review and Final Edition.
Municipal Solid Waste Management: Integrated Analysis of Environmental and
Economic Indicators Based on Life Cycle Assessment
Michel Xocaira Paesa,,b,*; Gerson Araujo de Medeiros b,*; Sandro Donnnini Mancinib;
Ana Paula Bortoleto c; José Antonio Puppim de Oliveira a,d,e; Luiz Alexandre Kulay f
São Paulo, Brazil;
Fundação Getulio Vargas (FGV), São Paulo School of Management (FGV/EAESP),
Institute of Science and Technology, São Paulo State University, Sorocaba, Brazil
School of Civil Engineering, Architecture and Urban Design, University of Campinas,
São Paulo, Brazil;
Administration (FGV/EBAPE), Rio de Janeiro, Brazil;
(USP), São Paulo, Brazil.
Fundação Getulio Vargas (FGV), São Paulo School of Management (FGV/EAESP),
Fundação Getulio Vargas (FGV), Brazilian School of Public and Business
School of International Relations and Public Affairs (SIRPA), Fudan University,
Chemical Engineering Department, Polytechnic School, University of São Paulo
*Corresponding authors: [email protected]
, [email protected]
Address: Unesp - Instituto de Ciência e Tecnologia - Câmpus de Sorocaba. Avenida
Três de Março, 511 - Alto da Boa Vista - Sorocaba/SP - CEP 18087-180
Tel.: +55 15 3238 3409 1
This paper develops a method to analyse municipal solid waste systems (MSWS) that
integrates environmental and economic indicators using Life Cycle Assessment (LCA)
and Life Cycle Costing (LCC). The method was tested in the city of Sorocaba, Brazil, a
medium size municipality typical of many developing countries. Environmental impacts
were analyzed considering system expansion, which combined the aspects of primary
production and recycling processes with the impacts of MSWMS. The economic
analysis included operating and investment costs to the costs of environmental
externalities, thus enabling the analysis of total costs to society. An integrated analysis
of environmental indicators revealed that the most significant reductions in
environmental impacts occurred in the scenarios with higher rates of reuse of dry waste
through recycling (70%), which lowered these impacts by up to 50% when compared to
the current scenario. An analysis of economic performance indicated that the two
scenarios that combined the highest recycling goals with greater transport efficiency and
more composting yielded the best results, reducing the total social costs by 31% and
33%, respectively. Lastly, the integration of environmental and economic analyses
revealed that the best results are obtained by a combination of composting, mechanical
biological treatment and recycling, which would reduce the impacts of MSWMS by up
to 33.7 points per invested dollar. The results supports the application of this proposed
integrate approach to improve the current solid waste management system in Sorocaba
and in other cities with a similar system and waste generation.
Keywords: Environmental Life Cycle Assessment; Life Cycle Costing; Environmental
and Economic Performance Indicators; Municipal Solid Waste Management; Public
Significant innovations in waste management have emerged in the last decade to
address the growing demand for materials and counteract the environmental and social
impacts of consumption-based economies (Cramer, 2013; Lauridsen and Jørgensen,
2010; Puppim de Oliveira, 2017, 2019). Programs involving zero waste and the
diversion of waste from landfills have gained momentum in response to increasing
urban densification and the growing value of space in the world’s largest cities.
Moreover, environmental regulations and the indisputable depletion of several material
resources confirm the benefits of converting end-of-life waste from anthropic processes
into inputs that can and should be reincorporated either into their own original
production cycles or into those of other producer or consumer goods (Andrews-Speed et
al., 2012; EEA, 2014; Paes et al., 2019).
Cities around the world have made a series of efforts to improve solid waste
management systems. In some EU countries such as Germany, Austria, Belgium,
Denmark, the Netherlands and Sweden, the implementation of public policies has raised
the rates of solid waste reuse, recycling, incineration (with energy recovery) and/or
composting to 95% (Eurostat, 2019; Word Bank, 2013). What all these cases have in
common is the adoption of practices for reduction, prevention and non-generation of
solid waste (Cleary, 2010, 2014; Nessi et al., 2012, 2013). In 2014, the United States
adopted the landfill alternative for 52% of their volume of solid waste, followed by
recycling (26%), incineration with energy recovery (13%) and composting (9.0%)
The most recent official estimates, published in 2017, indicated a daily
generation of 166,000 tons of municipal solid waste (MSW) in Brazil. Out of this total,
63% was landfilled, about 18% was discarded in open-air dumps without any treatment, 3
and 5.4% was treated in facilities for sorting, composting and recycling materials in
order to be recovered. However, no information was obtained from about approximately
14% of the waste generated (SNIS, 2019). In the state of São Paulo, which has the
highest gross domestic product (GDP) (US$ 527 billion) and the second-highest per
capita annual income in the country (US$ 12,075.00) (IBGE, 2019), about 50% of
MSW was generated in just nine of the 645 municipalities (State of São Paulo, 2015,
2017). In addition to sharing a similar urbanization profile, all these nine municipalities
now have more than 500,000 inhabitants. Among them is Sorocaba, the state’s ninth-
largest, covering an area of 456 km², with a population of 671,000 inhabitants and a
Human Development Index (HDI) of 0.798 (IBGE, 2019), whose economy is based on
Municipal or local governments in Brazil, similarly to many other countries, are
responsible for providing and controlling MSW management services. These actions are
based on legislation, management guidelines, objectives and targets at the local,
regional and national levels, which generally impose the challenge of rationalizing and
improving the performance of activities (Guerrero et al., 2013). The set of services,
infrastructure and operational facilities assigned to the activities of collection, transport,
sorting, treatment and disposal of solid waste in a municipality is called the Municipal
Solid Waste Management System (MSWMS) (e.g., Brasil, 2010; SNIS, 2019; World
Therefore MSWMS are complex and their effectiveness is not always easy to
measure, analyze and monitor. From the environmental standpoint, the Life Cycle
Assessment (LCA) technique has proved to be a suitable tool to evaluate their
performance, including the effect of actions and scenarios designed for their
improvement (Lazarevic et al., 2012; Paes et al., 2014, 2018). The scope of application 4
of LCA and the quantitative nature of its diagnoses enable the introduction of
comprehensive and accurate assessments in the daily routine of the management and
decision-making practices associated with these systems (Laurent et al., 2014; UNEP,
The economic performance of MSWMS has also been examined more recently
based on the concept of Life Cycle Thinking. Massarutto et al. (2011), Petit-Boix et al.
(2017) and Reich (2005), who used this approach, argue that the application of
traditional economic methods to systematic scopes, such as those practiced by LCA, can
offer useful findings for decision-making processes pertaining waste management
systems. These authors also point out that the inclusion of the costs of the use of natural
resources and pollution, known as negative environmental externalities, has proved to
provide important additional information that should be considered in future studies on
waste management, in addition to the operating and investment costs of these systems.
They also state that these environmental costs are rarely included and that to ensure
more accurate analyses of MSW management systems, these aspects should be studied,
developed, improved, valued and included.
The purpose of this study, therefore, is to make an integrated evaluation of
environmental and economic performance indicators of municipal solid waste
management systems by applying Environmental Life Cycle Assessment (LCA) and
Life Cycle Costing (LCC) approaches, enabling to structure more complete evaluations
of MSWMS so they can serve as guidelines to develop new public policies for
municipal solid waste management.
Therefore, this study aims to contribute to the advancement of knowledge
beyond the case study, by developing, building, applying and evaluating an innovative
method of integration and analysis of environmental and economic performance 5
indicators, which considers the operating and investments costs of environmental
externalities, in addition to total social costs, thus filling gaps within LCA and
management indicators of MSW.
The method involved the following steps: (i) choice of the case and
characterization of the MSWMS currently operating in the city of Sorocaba (SP), which
represents a good case to apply the method as the municipality has a set of data that can
be used in the analytical tools and the authors had access to the city´s data; (ii)
collection of data and information to underpin the establishment of a representative
model of the local management of MSW; (iii) diagnosis and evaluation of impacts
caused by the aforementioned MSWMS; (iv) proposal and specification of analysis
scenarios; (v) analysis of the environmental performance of these scenarios through the
identification of environmental impacts and definition of unique environmental
indicators for each scenario; (vi) examination of the economic performance of each
scenario based on its operating and investment costs and costs of environmental
externalities. This stage also involved the development of indicators of total social cost;
(vii) integration of the environmental and economic indicators pertaining to each
scenario, in order to make a simultaneous assessment of the influence of these
dimensions on the performance of the MSWMS, and (viii) proposal of guidelines aimed
at improving the system and that help support the formulation of public policies.
2.1 Characterization of the MSWMS of Sorocaba (SP)
Sorocaba, a municipality in the interior of the state of São Paulo (23° 30' 07” S,
47° 27' 28” O), covers an area of 456 km², has a population of approximately 670,000, 6
an industrial economy, and a Human Development Index (HDI) of 0.798 (IBGE, 2019).
In addition to the region’s economic relevance and the availability of data to conduct the
study, Sorocaba has solid waste management technologies that are commonly used in
Brazil, and its average recycling rate of approximately 3.0% is equivalent to that of the
national standard (PMS, 2014; Paes et al., 2018). These characteristics facilitate the
replication of research findings to regions with similar profiles.
Sorocaba’s MSWMS was characterized based on a survey of its MSW (i.e.,
volume of waste generation and gravimetric composition) and the technologies and
operational aspects of the system’s operation (Mantovani et al., 2016; Lima and
Mancini, 2017; Paes, 2018). To this end, recent data were collected along with official
documents, records of public hearings and meetings held with the drafting committee of
the Municipal Integrated Waste Management Plan.
The municipality generated an average of 184,508 tons year-1 of MSW in 2014.
These materials were collected in the form of ordinary garbage collection and selective
waste collection (PMS, 2014). Ordinary garbage collection in the municipality is carried
out from door to door, at different frequencies between the central region (six days
week-1) and other neighbourhoods (three days week-1). In this case, MSW is collected
from the generating sources and sent for final disposal in a landfill, without prior
sorting. The municipality has 25 collector-compactor trucks with a maximum load
capacity of 15 m³ (or 7.0 t) for ordinary garbage collection, each of which covers an
average daily distance of 160 km (Paes et al., 2018).
Sorocaba’s selective waste collection system covered only 15% of the houses in
the municipality. In this system, the MSW was sent for recycling after being separated
at sorting centres (PMS, 2014). This selective waste collection was carried out weekly
by worker cooperatives using 12 trucks with 4.0 t load capacity. Each of these trucks
covered an average daily distance of 36 km (Paes et al., 2018). Sorting was also done by cooperatives that owned the necessary equipment
(weighing scales, presses, forklifts and waste sorting tables) installed in five sheds.
The sanitary landfill for Sorocaba’s MSW covers a surface area of 617,000 m²,
with a capacity to receive 1000 t d-1 of material and an accumulation rate of 9,000,000
m³ of industrial and domestic waste during its service life (20 years). The landfill,
located 14 km from the city center, was equipped with liner and had systems for
collecting leachate and gases generated by the decomposition of organic matter. The
leachate was collected in basins and then transported to an effluent treatment plant. In
2014, the landfill gases were released into the air without treatment (PMS, 2014). Table
1 lists average daily data on the amount of non-recyclable waste, organic and recyclable
wastes generated in the municipality in 2014.
Separation and Marketing
Table 1. Characterization and type of waste collection, treatment, use and final disposal of MSW in
Sorocaba in 2014.
Source: Adapted from the Municipal Solid Waste Management Plan (PMS, 2014). CSA: Consórcio
Sorocaba Ambiental (Sorocaba Environmental Consortium), a group of companies that has the
concession and collects and hauls MSW in the municipality of Sorocaba (SP). CGA: Central de
Gerenciamento Ambiental (Environmental Management Center) – Sanitary Landfill
The data listed in Table 1 describe the three possible types of municipal solid
wastes (MSW) generated in Sorocaba: (i) Recyclables: plastic, glass, paper and metal
waste, as well as a variety of packaging, clothing, toys and electronic products sold for
reuse and recycling; (ii) Organics: including food and garden waste that can potentially
be reused through biological treatments such as composting and anaerobic digestion;
and (iii) Rejects: a fraction whose characteristics prevented it from being sold and/or
recycled in Brazil in 2014 (i.e., metallized films, certain types of glass, rubber, visibly
contaminated waste paper, thermosets, diapers, animal feces and contaminated toilet
paper) (PMS, 2014).
The total waste generated, reused/recovered/recycled and the waste sent to the
landfill were determined based on the gravimetric characterization of the municipality’s
MSW (Mantovani et al., 2016; PMS, 2014) and are described in the Supplementary
Material – Table A. This information served as the basis to develop of a model to
adequately and coherently represent the system, particularly in terms of resource
consumption (material and energy) and emissions.
2.2 Proposed Scenarios
Another bibliographical survey sought to identify management practices and
technologies that were not only consolidated and economically accessible but also had
not yet been applied in Brazil for MSW management. The management and planning
actions were translated into pre-established goals in the preliminary version of the
National Solid Waste Management Plan (Brasil, 2011) to reduce the amount of dry and
wet solid waste destined for landfills.
Technological actions refer to the practices of composting, mechanical
biological treatment (MBT) and incineration. These activities were characterized
considering the experience accumulated by the municipality of Barcelona, Spain, whose
environmental management structure – especially insofar as public solid waste
management is concerned – is considered a model among the countries of the European
Union (EC, 2019). Thus, in addition to official documents obtained from the Barcelona
City Council (AMB, 2013) and the company Tractament i Selecció de Residus, S.A.
(Tersa, 2014) and to scientific publications on the subject (Blanco et al., 2016; Colón et
al., 2012), fieldwork was also carried out to collect data and information describing
The combination of technological, management and strategic planning actions
led to eight operating scenarios for Sorocaba’s MSWMS. Scenario S1 corresponded to
the system operating in the municipality during 2014. The fact that S1 represents the
system’s actual operating condition means that it serves as the reference for comparison
of the environmental and economic performance of the other seven scenarios. Scenarios
S2 to S8 were designed from the composition of the goals established in the National
Solid Waste Management Plan and the treatment and final disposal alternatives that
could be incorporated into Sorocaba’s MSWMS. Table 2 summarizes the scenarios as a
function of the category of solid waste and the treatments employed.
Type of Waste/ Reject Dry
Wet Form of treatment/ final disposal
Recycling (%) 3.40
Landfill (%) 96.6
Incineration (%) 0.00
Composting (%) 0.00
Landfill (%) 100
MBT (%) 0.00
236 237 238 239
Table 2. General characteristics of each scenario concerning wastes and garbage disposal targets and options * The specificities of these scenarios are discussed below throughout the article. MBT: Mechanical Biological Treatment
The selective waste collection system was used in scenarios S1 to S5 to collect
the MSW destined for the sorting and composting units. The average fuel consumption
of ordinary garbage collection was estimated at 2.43 L/t MSW and that of selective
waste collection at 7.06 L/t MSW, based on the study by Paes et al. (2018). For
scenarios S6 to S8, it was stipulated that all forms of collection and transportation
would have the same consumption as that of the conventional garbage collection system
(2.43 L/t MSW). Table B (Supplementary Material) shows the quantities of transported
waste and the diesel fuel consumed by the solid waste collection system of each
In the specific case of S7, the targets remain the same, but all plastic and paper
waste was destined for incineration. In the case of S8, decentralized composting of 10%
of the wet wastes were included (to be carried out at the sites of origin, such as gated
communities, neighbourhoods, schools and public spaces in the city). Consequently, it
would forestall the transportation and use of waste treatment units considered in this
study for this fraction of wastes. Table C (Supplementary Material) presents the actual
indices of final disposal, in annual quantities, and reuse of material in each scenario.
2.3 Life-Cycle Modeling
The environmental performance was determined based on an attributive LCA
with a cradle-to-grave approach, according to the ISO 14044 standard (ISO, 2006).
Thus, the Functional Unit (FU) for the study was defined as “Management of the
activities of collection, transport, sorting, recycling, treatment and final disposal of
184,508 t year-1 of MSW generated by the municipality of Sorocaba, Brazil.” Figure 1
presents the Boundary System of Sorocaba’s MSWMS with its various stages and
Figure 1. Schematic representation of the Product System comprising Sorocaba’s MSWMS
The stages of the ordinary garbage collection, selective waste collection, sorting
and final disposal in a landfill were characterized based on primary data obtained from
Lima and Mancini (2017), Mantovani et al. (2016), and Paes et al. (2018), as well as on
fieldwork with the Municipal Government of Sorocaba (PMS, 2014).
Data on energy and water consumption and greenhouse gas (GHG) emissions
pertaining to the processes of primary production (comprising the steps of extraction of
raw material and manufacture of products from virgin raw material) and recycling of
metals, plastics, paper and glass, were garnered from official publications of Brazil’s
federal government (IPEA, 2010 and EPE, 2014).
Consumption and emissions data pertaining to the MSW treatment technologies
(composting, MBT and incineration) not yet used in Brazil were obtained through
primary and secondary data, as indicated in section 2.2 – AMB (2013), Blanco et al.
(2016), Colón et al. (2012) and TERSA (2014). The MSWMS data from both Sorocaba
and Barcelona were based on the guidelines defined by Doka (2009a, 2009b, 2009c) to
model the diagnoses (S1) and scenarios (S2 to S8).
Following the guidelines of Brogaard (2013) and Laurent et al. (2014), the
Product System models for the analysis scenarios also considered environmental
burdens relating to utilities (electricity generation and distribution, treatment of water
and liquid effluents), facilities and infrastructure (construction and maintenance of
capital goods and roadways). The same applies to the life cycle of diesel oil used by
machinery and trucks.
Thus, secondary data were used for the environmental aspects about the life
cycle of transport activities (such as construction and maintenance of trucks and
roadways, and petroleum refining for diesel oil production). These data were garnered
from the Ecoinvent database, in the form of the following datasets: ‘transport, waste
collection lorry 21t/ADAPBR U’; Diesel at regional storage/ADAPBR U; Operation
maintenance/ADAPBR/I U, road; Road/ADAPBR/I U’ created by Doka GmbH (2009a,
As for data quality, the geographic coverage consists of the municipality of
Sorocaba, and the year 2014 was established as to temporal coverage for this study. The
technology coverage comprises two complementary approaches. The first one refers to
Sorocaba’s MSWMS, which was specified for this dimension based on the operations,
practices, procedures and aspects of infrastructure it comprises. The second approach
focuses on technologies such as composting, MBT and incineration, for which the
experience and practices of the city of Barcelona were adapted.
Lastly, the methodological stage of the Life Cycle Impact Assessment was
carried out using the ReCiPe MidPoint V1.13 method (EC, 2010a, Goedkoop, 2009).
This stage involved an individual evaluation of the impact categories of Climate Change
(CC), Acidification (AC), Eutrophication (EUT), Particulate Matter (PM) and Human
Toxicity Potential (HTP), which were then normalized to analyze the contribution of
each category of impact from the MSWMS. These categories were chosen because they
are frequently used in LCA studies involving solid waste management, as presented by
Laurent et al. (2014) and Bernstad and Jansen (2012).
The situations of multifunctionality that occurs in the scenarios described in
section 2.2 were treated by cross-border expansion. In this context, following the
methodological guidelines proposed in Laurent et al. (2014) and the ILCD Handbook
(EC, 2010b), environmental load substitution procedures were used for the recycling of
metal, plastic, paper and glass waste and energy recovery in the situations of a sanitary
landfill, MBT and incineration.
The data considered for recycling processes were water and energy consumption
and CO2-eq (carbon dioxide equivalents) emissions. In primary production, which
comprises the stages of raw material extraction and product manufacturing from virgin 14
raw material, official data on water and energy consumption and CO2-eq emissions
published by Brazil’s federal government were also included, as illustrated in Figure 1
(IPEA, 2010 and EPE, 2014).
The consumption and emissions (from primary production and recycling
processes) were calculated concerning waste materials with a potential for reuse but that
was discarded in the landfill, in addition to those that were the object of selective waste
collection and sorting and sent for recycling.
Secondary raw materials were assumed in this study to be able to substitute
virgin raw materials reducing environmental impacts without compromising the product
quality. Raw materials extraction rates, however, were not expected to reduce or to
increase since it also depends on consumption demand for these products.
The transport stages about the two processes were not considered in this stage of
the study because they were not directly linked to public policies and services but were
conducted by private enterprise, making it difficult to obtain accurate estimates in this
Hence, it had to be assumed that the reinsertion of a secondary/recyclable
product into the production chain would prevent the environmental impacts resulting
from the production of goods from virgin raw material. For instance, by recycling steel
or aluminum can, it would no longer be necessary to extract the corresponding amount
of iron ore or bauxite to produce a new can from these metals. The same applies to the
power generated by waste treatment and disposal units (i.e., Landfill, MBT and
Incineration). Thus, in terms of MWh generated, the study considered that the
consumption of electricity from the Brazilian energy matrix, which is predominantly
hydraulic, would be avoided.
It should be noted that, despite the cross-border expansion, the environmental
burdens (generated and avoided) and the costs of energy generation remained within the
MSWMS. Conversely, the environmental burdens (generated and avoided) resulting
from primary production and recycling processes were analyzed separately, and their
operating and investment costs were not considered since they were also covered by the
private sector and not directly by public policies for MSW.
The data on energy (MWh) and water (m³) consumption and GHG emissions
(tCO2-eq) in each scenario (S1 to S8), described in Table D of the Supplementary
Material, were multiplied by the annual total of the materials/wastes sent to final
disposal (landfill and incineration, thus requiring new raw material and product) and
sorting/recycling units (avoiding primary production processes). Thus, it was possible to
make a quantitative estimation of these consumptions and emissions that were
effectively incorporated by the actions, and that could be adopted by the MSWMS, by
reusing more significant fractions of these dry wastes and recyclable materials.
2.4 Analysis of Economic Performance
The economic analysis of this study was made through the concept of Life Cycle
Costing (LCC). This concept can be defined as an evaluation of all the costs associated
with a product’s life cycle, which are supported directly by a given stakeholder, with the
complementary inclusion of externalities that can be internalized in the future and that
are relevant to decision making (Hunkeler et al., 2008; UNEP, 2011).
The use of the concept of LCC predates that of the Environmental LCA, and
these two methods have been integrated to a certain extent, although the value of LCC
for sustainability assessments has been recognized and used (Hunkeler et al., 2008;
Iraldo et al., 2017; Swarr et al., 2011). 16
Therefore, this study was based on bibliographic reviews and methodological
guidelines that emphasize the need to consider not only operating costs but also the
costs of externalities identified in a given system, and that could be internalized by the
actors, in this case by public policies toward solid wastes. Iraldo et al. (2017), Moreau
and Weidema (2015) also point out that further advances are needed in these subjects
and that, to this end, studies must be developed aimed at expanding this area of
knowledge in order to fill these gaps in the field of LCA and LCC.
Based on the scenarios and results of the inventories of environmental LCA, this
study used data on operating and investment costs of the MSWMS (PMS, 2014;
BNDES, 2014), as well as costs of environmental externalities pertaining to the
environmental aspects of energy and water consumption and GHG emissions (IPEA,
2010; EEA, 2016). The sum of operating and investment costs with those of
environmental externalities made up the total social costs, based on the concepts and
definitions of Life Cycle Costing (i.e., Martinez-Sanchez et al., 2016; Petit-Boix et al.,
The MSWMS operating costs of 2014 (PMS, 2014) were considered to estimate
the costs of ordinary and selective waste collection, sorting and final disposal of MSW
in a landfill. The operating and investment costs of composting, MBT and incineration
units were estimated based on official data for the year 2014 about the costs of
implementing and operating these waste treatment technologies in Brazil (BNDES,
The costs of environmental externalities of energy generation in Brazil were
estimated based on data from IPEA (2010). The average value defined by these studies,
updated for the year 2014, such as environmental costs per MWh of energy, was US$
Data published by IPEA (2010) were also used to determine the values of
environmental costs of water resources. This study used as reference the valuation
methods and the established prices for the use of water by the country’s river basin
committees. These prices reached an average of US$ 0.33 per m³ of water, also updated
for the year 2014.
Lastly, the current market value of the emission permit for one ton of carbon
equivalent expressed in t.CO2-eq was used for the GHG. The average price of the
equivalent ton of CO2 for the year 2014 was US$ 9.04 per t.CO2-eq (EEA, 2016).
The operating and investment costs (O&IC) were calculated based on the values
per ton of treated waste – according to the value of each treatment unit (US$.unit) –
multiplied by the quantities of waste destined for the units (t.MSW) of each scenario
(Sc). The same procedure was adopted for transport, and the costs per ton of transported
waste (US$.modalTransport) were multiplied by the amount of waste collected by each
mode of transport (t.MSW) in each scenario (Sc). These calculations are illustrated by
equation (1) and also described in detail in Table E (Supplementary Material).
The unit costs of environmental externalities (CEE), presented previously, were
also multiplied by the water (C-m³) and energy (C-MWh) consumption rates and the
annual emissions of GHG (E-CO2-eq.) in each scenario (Sc), according to equation (2):
The economic benefits (BE) resulting from the energy (KWh) generated by the
waste treatment units in each scenario (Sc) were multiplied by the annual average price
of electricity (US$/kWh) in the region under study, determined by means of fieldwork
and from bills paid by the municipality, as presented in equation (3). The average
annual price paid by the municipality understudy in 2014 was US$ 0.139/MWh.
( = )
423 424 425
E (Supplementary Material) also describes details of the values and calculations. Lastly, the Total Social Cost (TSC) was calculated using equation (4):
– ( +
Quantitative data on water and energy consumption and emissions of CO2-eq. of
the externalities of the MSWMS (for each scenario) are also described in Section 3 –
Life Cycle Inventory (LCI).
For the primary production and recycling externalities, the values listed in Table
D – Supplementary Material (Substitution of Environmental Burdens) were multiplied
by the quantity of dry wastes sent to the final disposal units (landfill and incineration,
which would thus require new raw material and product) and sorting/recycling
(avoiding primary production processes), and are described in detail in Table E of the
The quantities of waste sent to each of the treatment units (which were used to
calculate the Operating & Investment Costs) are listed in Table C (Supplementary
Transport is also explained by the criterion presented under subsection 2.2.
According to this criterion, in scenarios S1 to S5, the waste destined for the sorting and
composting units was transported via the selective waste collection system (and to the
other units, such as landfill, MBT and incineration, via the ordinary garbage collection
system). In scenarios S6 to S8, the costs of all forms of collection and transportation
were assumed to be the same as that of the ordinary garbage collection system. The
results of this procedure and calculations are also listed in Table B of the
449 450 451
3 RESULTS AND DISCUSSION
3.1 Life Cycle Impact Assessment (LCIA) 3.1.1
Life Cycle Inventory and Characterization Method
The Life Cycle Inventory (LCI) data of the MSW treatment and disposal units
using the input and output flows for each of the scenarios, based on the functional unit
adopted in this study and on the information presented under subsection 2.3, are
describes in Table F (Supplementary Material).
The quantification and analysis (through the characterization method) of the
contributions of each MSWMS activity to the environmental impacts considered in this
study – Acidification, Eutrophication, Climate Change, Particulate Matter and Human
Toxicity Potential – are presented in a relativized way in Table G (Supplementary
Method of Normalization and Construction of a Single Environmental
Indicators for the Waste Management System
The scenario S1 presented a total score of 42,251, while all the other scenarios
showed performance improvements. In this case, the total impacts were reduced by 38%
in S2, 52% in S3, 34% in S4, 40% in S5, 46% in S6, 49% in S7, and by 52% in S8.
In scenario S1, the main contributions in terms of environmental impacts were:
climate change (60%), followed by particulate matter (14%), acidification (10%),
human toxicity potential (9%) and eutrophication (7%). In S2, contributions to total
impacts were ascribed to climate change (39%), acidification (30%), particulate matter
(24%), human toxicity potential (5%), and eutrophication (2%).
The main contributions to total environmental impacts of scenario S3 would
come from acidification (43%), particulate matter (32%), climate change (22%), human
toxicity potential (5%), and eutrophication (-2%). This scenario presented impacts
avoided by generating electrical energy from waste treatment and disposal units, thereby
contributing to reducing the use of hydroelectric sources (which predominate in Brazil’s
electricity matrix) and thus reducing the environmental impacts of eutrophication. In
scenario S4, which would also dispose of MSW in a landfill, the main contributions to
the total environmental impacts would be due to acidification (39%), particulate matter
(25%), climate change (24%), human toxicity potential (7%) and eutrophication (4%).
In S5, contributions to the total environmental impacts would come from
acidification (45%), particulate matter (29%), climate change (17%), human toxicity
potential (7%), and eutrophication (4%). In S6, the main contributions to total
environmental impacts would be caused by acidification (48%), particulate matter
(29%), climate change (16%), human toxicity potential (6%), and eutrophication (2%). 21
In S7, the main contributions to total environmental impacts would come from
acidification (50%), particulate matter (30%), climate change (16%), and human
toxicity potential (5%), while eutrophication would be lower by (-)1. Lastly, the main
contributions in S8 would come from acidification (47%), particulate matter (29%),
climate change (16), human toxicity potential (6%) and eutrophication (0.1%).
Figure A (Supplementary Material) illustrates the overall environmental effects
using a single normalized MSWMS indicator, depicting the contributions of each
impact category (Acidification, Eutrophication, Climate Change, Particulate Matter and
Human Toxicity Potential) for all the scenarios created in this study.
This procedure revealed that the environmental performance of the MSWMS
could be improved by adopting measures aimed at greater reuse and treatment of
municipal solid waste, allied to improvements in the efficiency of the selective waste
collection system. Electric power generation and its impacts avoided through MBT and
incineration contributed to the good results of scenario S3 (particularly in terms of
eutrophication) while composting at the MSW generation sites also contributed to the
results of scenario S8.
Recycling and Primary Production Indicators
This section discusses the potential environmental impacts of CO2-eq. emissions
and the water and energy consumption of the processes of primary production and
recycling of dry waste, which were defined and considered by the environmental load
substitution method and cross-border expansion (see subsection 2.3).
Table H in the Supplementary Material analyzes the contributions of the
environmental aspects about water and energy consumption and GHG emissions to each
impact category considered here (i.e., Acidification, Eutrophication, Climate Change,
Particulate Matter and Human Toxicity Potential). And Figure B (Supplementary 22
Material) illustrates the total impacts and contributions of each impact category
examined in this study, considering recycling and production of virgin raw material.
As can be seen in Figure B (Supplementary Material), what stands out in this
stage of the study is the reduction of environmental impacts. This is demonstrated, using
the single indicator/ normalization method, in scenarios S4, S5, S6 and S8, which have
the highest reuse rates of dry recyclable waste (70%), followed by scenarios S2 and S3,
in which the reuse rates are lower (41%).
Scenario S1 (which was in operation in the year 2014), presented a total score of
193,099 and the worst result. Scenarios S2 and S3 showed a reduction of 34% in total
impacts. Still in comparison with S1, scenarios S4, S5, S6 and S8 showed a 52%
reduction in total impacts. The least significant impact reduction, 18%, was reached in
Scenario 7 due to the incineration of plastics and paper, which caused impacts because
of the need for primary production of these raw materials.
All the analyzed scenarios showed similar contributions from each
environmental impact category. The impact categories with the highest contributions to
the total impacts were Eutrophication (44% to 45%), followed by Human Toxicity
Potential (34%), Climate Change (7% to 8%), Particulate Matter (7%) and Acidification
(6%). These impacts were influenced mainly by energy consumption – through Brazil’s
hydroelectric matrix – by primary production and recycling activities, followed by CO2-
eq. emissions and water consumption, which are listed quantitatively in Table H of the
Establishment of the Single Indicator
The data presented in Figure A (Supplementary Material) - Indicators for the
Waste Management System - were then combined with those in Figure B
(Supplementary Material) - Recycling and Primary Production Indicators -, enabling the 23
development of a single indicator by the normalization method to analyze
environmental performance based on cross-border expansion. Figure 2 shows the scores
for each scenario, impact reductions and resulting improvements in environmental
performance compared to that of the scenario in operation in 2014 (S1).
Total Primary Production and Recycling
Total Product System
Figure 2: Environmental Performance of the MSWMS, the Primary Production and Recycling Processes
and the complete Product System adopted.
Figure 2 clearly shows that the results were more satisfactory for recycling,
based on the sum of the scores of the MSWMS indicators with cross-border expansion
for the primary production and recycling activities. This was mainly due to the
scenarios that considered greater reuse of dry waste by recycling technologies, such as
scenarios S4, S5, S6 and S8, which afforded environmental impact reductions of 49%,
50%, 51% and 52%, respectively, when compared to S1. The scenarios involving lower
targets for reuse of dry waste, such as S2 and S3, provided lower impact reductions of
35% and 37%, respectively. The lowest total impact reduction was achieved by scenario
S7, i.e., 24%.
Also to be noted is the positive contribution of transport in response to the
adoption of the efficiency of ordinary garbage collection for the selective waste
collection system. Moreover, impacts were avoided through the generation of electricity
by waste treatment units and the adoption of preventive measures via composting at the
sites of wet waste generation, as described in subsubsection 126.96.36.199 and in Table G and
Figure A (Supplementary Material).
Averaging the score of the eight scenarios revealed that the impacts of the
MSWMS contributed 1/5 (18%) to the total impacts, while 4/5 (82%) would be due to
the impacts of cross-border expansion through consumption and the emissions produced
by primary production and recycling. In other words, more than merely collecting
MSW, society’s profile of consumption and waste disposal, as well as the decision
about what to do with discarded waste, have a significant environmental impact.
3.2 Life Cycle Costing (LCC)
Calculations of Financial and Environmental Life Cycle Costing are presented
below (Table 3) based on the results of Operating & Investment Costs, Environmental
Externalities and Total Social Costs for each of the scenarios.
Table 3: Operating & Investment Costs of the MSWMS (US$/year); Costs of the Environmental Externalities of primary production (PP) plus recycling (R) and of the MSWMS and; Total Social Costs (US$/year) for all the scenarios. Scenarios Ordinary Collection (t)
Selective Collection (t)
Subtotal MSWMS (-) Generated Energy (kWh) Total Costs MSWMS
574 575 576 577 Scenarios Energy (MWh) Water (m³) CO2eq (t) Subtotal Externalities PP + R Energy (MWh) Water (m³)
Subtotal Externalities MSWMS
Total Costs for Society
As can be seen in Table 3, the scenario in operation in 2014 (S1) had a lower
annual operating cost of approximately US$ 25.7 million. However, it caused a more
significant environmental externality of approximately US$ 50.5 million per year,
resulting in an annual social cost of US$ 76.2 million, the highest of all the scenarios.
In scenario S2, with composting and recycling (in the range of 40%) plus
landfilling, the annual costs and investments increase by 30%, but the externalities
decline by approximately 34% compared to S1. Scenario S3 (which has the same
recovery targets via composting and recycling as those of S2, plus MBT and
incineration of the remainder rather than landfilling), would show an increase of 37% in
annual operating costs and a decrease in externalities similar to that of S2, i.e., 34%.
Total social costs would decrease by 13% in S2 and by 10% in S3.
It is noteworthy that, based on investments in greater reuse of recyclable
materials (through the targets of 70% recovery), like in Scenarios 4 and 5, the annual
operating costs would increase by 47% and 53%, respectively (compared to S1).
However, the externalities would decrease by 52% and 51%, respectively, resulting in a
total social cost reduction of 18% in S4 and 16% in S5.
When the level of efficiency of ordinary garbage collection is considered for
selective waste collection, scenario S6 shows a lower increase in operating and
investment costs than the preceding scenarios (S2, S3, S4 and S5), with an increase of
8% in comparison to the scenario in operation in 2014 (S1). Scenario S6 would also
have a decrease of 51% in the costs of externalities and 31% in total social costs
compared to those of S1.
Scenario S7, whose characteristics are the same as those of S6, but also
incinerates all paper and plastic wastes, shows a 7% increase in operating and
investment costs, but a lower reduction in externalities costs (18%) and the same 28
reduction in total social costs (10%) as S3. Lastly, S8, a scenario similar to S6, but
which adds composting of 10% of organic wastes at the generation sites, shows the
lowest increase in operating and investment costs (3%) and the most significant
reduction in total social costs (33%). Compared to S1, this scenario also presents a 51%
decrease in the costs of environmental externalities.
In summary, the results suggest economic gains obtained through the adoption
of practices that reduce negative environmental impacts, such as recycling, composting
(mainly when decentralized) and MBT, in detriment to incineration and especially
landfilling. Based on this curve, the worst scenario is S1, followed by S3, S7, S2, S5,
S4, S6 and S8. The latter shows the best economic performance of all the scenarios,
with total social costs of US$ 51.1 million compared to US$ 76.2 million of the scenario
operating in 2014, i.e., 1/3 lower.
3.3 Integration of Indicators and Scenarios in LCA to establish Public Policies
for MSW Management
The inventory and the environmental impact assessment and Life Cycle Costing
methods revealed a direct relationship between the improved efficiency of the MSWMS
and the increase and better management of costs and investments. Such investments
would lead to reductions not only in the environmental impacts of the MSWMS itself
and of the affected systems (recycling and primary production), but also in the costs of
environmental externalities. Figure 3 illustrates the correlations of the results, providing
a more detailed picture of how operational investments are reflected in environmental
indicators and externalities costs.
Environmental Performance - Normalization (Primary Production + Recycling)
Environmental Performance - Normalization (MSWMS)
S2 S6 80,000.00
Operational and Investments Costs of MSWMS (1,000 dolllars)
Operational and Investments Costs of MSWMS (1,000 dollars)
(C) Environmental Externalities Costs (1,000 dollars)
Operational and Investments Costs of MSWMS (1,000 dollars)
Figure 3: Correlations between Operating & Investment Costs and Environmental Impacts of the MSWMS (A), Impacts of Primary Production and Recycling (B) and Costs of Environmental Externalities (C).
Thus, upon adopting the correlation between the reduction in environmental
impacts of the MSWMS and the invested monetary value (Figure 3A), there is a
reduction of 33.7 points/dollar invested in S8, followed by a reduction of 12
points/dollar invested in S7 and 10.1 points/dollar invested in S6. Also note, in Figure
3A, that these scenarios (S6, S7 and S8) are closest to the lowest costs (x-axis) and
environmental impacts (y-axis). The other scenarios would lead to reductions of 2.1
(S2), 2.3 (S3), 1.2 (S4) and 1.3 (S5) points per dollar invested.
Based on an evaluation of the impacts of primary production and recycling
(Figure 3B), upon also adopting the correlation of impact reduction per invested dollar,
one can see that better results would show a reduction of 152 dollar points/dollar
invested (S8) and 50.9 points/dollar invested (S6). Scenario S7 would show a reduction
of 20.1 points/dollar invested, while the other scenarios show the following
relationships and reductions: 8.7 points/dollar invested (S2); 6.9 points/dollar invested
(S3); 8.3 points/dollar invested (S4) and 7.3 points/dollar invested (S5).
An analysis of the reductions in the costs of environmental externalities per
dollar invested in the MSWMS (Figure 3C) indicates that scenario S8 also presents the
best result, with a reduction of 39 dollars per dollar invested, followed by S6, with a
reduction of 13 dollars per dollar invested, and S7, with a reduction of 5 dollars per
dollar invested. The other scenarios show a ratio reduction of 2 dollars per dollar
Thus, by means of S7 (Figure 3A), in which primary production and recycling
processes were not considered through the method of cross-border expansion and
substitution of environmental burdens, heat treatment may reduce the impacts of
MSWMS, especially those resulting from atmospheric emissions and the avoided
burdens of using electric power, as demonstrated in greater detail in subsubsection 31
3.1.2. However, considering the entire product system analyzed here, Figures 3B and
3C clearly demonstrate that the indicators show better results, especially in scenarios S6
and S8, both of which adopt not only improvements in the selective waste collection
system but also zero landfilling and the highest recycling and composting rates
considered in this study (70%). Of these two scenarios, S8 is even better, because it
differs in that part of the composting takes place at the waste generation sites, thereby
reducing transport-related impacts.
The above-described procedure revealed the importance of integrating the
analysis of operating and investment costs with environmental indicators and
externalities costs. The use of the cross-border expansion method and the substitution of
environmental burdens from primary production through recycling enabled us to
determine how both the environmental performance and the costs of environmental
externalities of the MSWMS are related to its efficiency and investment spending.
Based on the results presented herein, the Life Cycle Impact Assessment and
Life Cycle Costing techniques proved to be suitable for the analysis of scenarios and
can, therefore, be used as management and decision making tools for public policies on
MSW management (i.e. Silva et al., 2017; Xu et al., 2018). These techniques enabled
the proposal of management guidelines and actions aligned with national laws and
international best practices and trends (i.e. Brockmann et al., 2018; Restrepo and
Morales-Pinzón, 2018; Santos et al., 2018). These best practices and trends include the
Promote the expansion and improvement of Selective Waste Collection, Sorting
and Recycling systems by increasing the efficiency of selective waste collection
transport systems and implementing actions aimed at gradually, albeit rapidly,
increasing and universalize selective waste collection, sorting and recycling services; 32
Establish progressive incentives to those that implement local alternatives for
waste management and treatment, such as reduction and/or exemption of the “solid
waste fee” for gated communities, subdivisions, neighbourhoods and residences that
adopt not only the selective waste collection but also onsite composting. Another
alternative would be to implement a system known worldwide as PAYT, an acronym
for Pay As You Throw (i.e., EPA, 2006), which could encourage sites that adopt waste
reduction and prevention measures;
Promote the Reuse and Treatment of MSW, based on the economic instruments
set forth in the National and Municipal Climate Change Policy (Brasil, 2009; PMS,
2016), This could be done, for example, through tax, fiscal, financial and economic
incentives for management systems and technologies that produce lower GHG
emissions and for carbon credit projects and the Clean Development Mechanism
(CDM). However, note that this item and action should be a topic and subject of
discussion by municipalities at the national and state levels of government, through the
establishment of broader laws to incentivize technological and management alternatives
that contribute to expanding the reuse of solid waste;
Implement decentralized actions in MSW management, aimed at broadening
participation of the population through local alternatives that contribute to reducing the
amount of MSW sent to collection, transportation and waste disposal systems, such as
Reduce the environmental impacts of waste disposal systems predominantly
used in Brazil (Sanitary Landfills), by burning the methane (CH4) emanating from
landfills and using it to generate energy.
Thus, this study is expected to be useful for similar local and MSWMS
managers in terms of actions aimed at improving their systems and in the developing of 33
public policies that deal with the (complex) issue of MSW. Discussions to improve
MSWMS have converged in the identification of the potential of management
technologies and practices aimed at reducing the environmental and economic impacts
of waste management.
This study has limitations in its analytical approach as the model only integrates
environmental and economic performance indicators. Contextual and social aspects,
such as consumption rates or health issues, were not considered since more detail
analytical approach for social life cycle assessment are still in progress (e.g., Jørgensen
et al., 2008). Future studies should consider to apply this method for solid waste
The integration of economic and environmental indicators through the Life
Cycle Thinking provides coherent diagnostics of complex and broad systems. In the
same way, this approach is effective in establishing scenarios that can underpin
adequate long-term planning of public policies in the MSW domain.
By considering other processes, procedures as system expansion and the
substitution of environmental loads, adopted to solving multifunctional situations,
proved to be fundamental for understanding of activities that are (or may be) affected by
decisions relevant to MSW management.
The MSWMS option that maximized recycling of dry waste and composting of
wet waste, which was partially carried out on-site, presented the best ratio between
environmental impacts and total social costs. Conversely, when one considers only
operating and investment costs, the scenario composed by landfilling (96.6% of waste
disposal) and recycling (3.4%), is the cheapest alternative, which is why it is frequently 34
adopted in most of developing countries, including Brazil. However, the economic
benefits achieved with less impacting scenarios compensate the higher investment and
operating costs required by them, providing advantages even for economies that are still
in the process of establishment.
As mentioned before, this study can subsidize MSWMS public managers from
similar municipalities as Sorocaba in terms of both establish actions aimed at improving
their systems and in the developing of public policies that deal with such (complex)
issue. Moreover, limitations as absence of some important social aspects – e.g.
consumption rates or health issues –, should be surpassed in future studies in order that
diagnosis like this could even more fully and consistently support the formulation of
public policies on the topic.
The autors would like to express gratitude to CAPES (Coordenação de
Aperfeiçoamento de Pessoal de Nível Superior) for the doctoral fellowship and
FAPESP (São Paulo Research Foundation) for the postdoctoral fellowship awarded to
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A tool for solid waste management performance analysis based on LCA is presented
Operating costs, externalities and total social cost were obtained and analyzed
Economic and environmental issues of each option were examined in an integrated way
The best option combines composting, mechanical biological treatment and recycling
Impact decrease was up to 34 points/US$ invested compared to the current situation
List of abbreviations Acidification (AC) Clean Development Mechanism (CDM) Climate Change (CC) Environmental Life Cycle Assessment (LCA) Eutrophication (EUT) Functional Unit (FU) Greenhouse Gas (GHG) Gross Domestic Product (GDP) Human Development Index (HDI) Human Toxicity Potential (HTP) Life Cycle Costing (LCC) Mechanical Biological Treatment (MBT) Municipal Solid Waste (MSW) Municipal Solid Waste Management Systems (MSWMS) Particulate Matter (PM) Pay As You Throw (PAYT)
Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: